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deepseek_harness

deepseek_harness

by XiangyunHu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

submit_task

Start a coding task and return immediately; queue scoped jobs for an asynchronous worker agent that edits code and runs tests using workspace instructions and acceptance criteria.

Instructions

Start a coding task and return immediately. Multiple tasks may queue or run.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspace": "<workspace>",
      "instruction": "<instruction>",
      "acceptance": "<acceptance>"
    },
    "name": "submit_task"
  }
}

Input Schema

NameRequiredDescriptionDefault
workspaceYes
acceptanceYes
instructionYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose the key behavioral trait of asynchronous submission ('return immediately') plus concurrency/queueing behavior. It says nothing about idempotency, duplicate submissions, permissions, or failure modes, so a mutation-triggering tool remains only partially characterized.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with zero filler, and the async return behavior is front-loaded where it matters most for an agent deciding how to proceed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema presumably documents the returned task handle, so return values need not be explained, and the async semantics are covered. But with no annotations and 0% parameter coverage, the definition leaves the agent guessing about inputs and side effects for a tool that kicks off background work.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across three required parameters (workspace, instruction, acceptance), and the description adds no meaning for any of them. The names are partly self-explanatory, but the shape of 'acceptance' (a string array, presumably criteria) and what 'workspace' refers to are left entirely undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource ('Start a coding task') and adds the async qualifier 'return immediately,' which distinguishes it from the blocking sibling wait_task. It stops short of naming or explicitly contrasting with continue_task or cancel_task, so differentiation is implied rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Return immediately' plus 'Multiple tasks may queue or run' implies the fire-and-forget pattern where the agent later polls with get_task/wait_task, which is useful implied usage guidance. However, there is no explicit when-to-use versus when-not, and no mention of when continue_task would be the right choice instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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